ORLEN Skylight accelerator

We are looking for innovative solutions that enable the optimization of flare system operations and the efficient management of gas streams directed to flaring. The goal of the challenge is to reduce utility consumption (in particular steam), minimize feedstock losses, and limit environmental impact, while maintaining the highest level of process safety.

The challenge includes solutions that enable:

• optimization of flare system performance based on real-time operating conditions,
• adjustment of steam consumption to the variable volume and composition of gases routed to flares,
• monitoring, identification and diagnostics of gas release sources,
• analysis of the composition of gas streams directed to flaring,
• operator support through recommendation systems that improve efficiency and safety,
• reduction of emissions and production losses associated with flaring,
• utilization of off-gas streams through recovery of valuable components (e.g. hydrogen, light hydrocarbons).

A key requirement is the ability to deploy the solution within existing infrastructure without interference with core production systems, as well as flexibility to handle highly variable gas stream parameters.

We are looking for both digital solutions (AI, Digital Twin, advanced analytics) and technologies enabling the recovery and utilization of gaseous waste streams.

We are looking for innovative solutions that enable mobile and flexible generation of process steam in industrial facilities. The goal of the challenge is to ensure continuity of steam supply in situations of variable and localized demand: particularly during maintenance, start-ups, and unplanned shutdowns; through the use of mobile, containerized generation units.

The solution should allow for rapid deployment and temporary installation in different areas of the plant, depending on current operational needs.

We expect solutions that:

• provide mobility and ease of relocation (e.g. container-based units),
• enable fast start-up and flexible adaptation to changing steam demand,
• support the use of multiple fuel types (e.g. natural gas, refinery gas, diesel, optionally hydrogen),
• meet high safety requirements, including the ability to operate in hazardous (ATEX) environments,
• can be integrated with existing plant infrastructure without significant modifications.

We are looking for technological solutions that can complement or support existing process steam generation systems.

We are looking for innovative solutions enabling efficient thermal integration of industrial processes and effective utilization of waste heat in industrial installations.

The goal of the challenge is to improve energy efficiency through the recovery, exchange, processing, and reuse of thermal energy from various process and steam streams, particularly low-temperature waste heat that currently remains largely unused.

In many industrial processes, there are simultaneous streams requiring heat removal and others requiring heat input. Their effective integration and utilization of available energy potential can significantly reduce commercial energy consumption, improve the energy balance of installations, and minimize process losses.

The challenge includes solutions that enable:

• efficient heat exchange between various process and steam streams,
• recovery and utilization of waste heat, particularly in the low-temperature range (approx. up to 60°C, 90°C, and 110°C),
• upgrading the temperature or other parameters of process media using available energy streams,
• conversion and utilization of recovered heat in technological processes, heating systems, or auxiliary installations,
• application of innovative heat exchange technologies, including advanced or non-standard heat exchangers,
• integration with existing process infrastructure without significant modifications,
• flexible adaptation of the technology to different operating conditions and installation configurations.

The scope of the challenge excludes ORC (Organic Rankine Cycle) technologies.

We are looking for both technological and system-level solutions enabling a comprehensive approach to thermal energy management in industrial facilities.

We are looking for innovative solutions enabling heat recovery from flue gases discharged through stacks in industrial installations. The goal of the challenge is to utilize the thermal energy contained in flue gases, which currently remains largely unused, by recovering and reusing it in technological processes or auxiliary systems. The expected outcome is improved energy efficiency and reduced consumption of commercial energy sources.

A key challenge is the requirement to operate in acidic environments resulting from the presence of sulfur compounds in flue gases. This requires the use of corrosion-resistant materials and technologies ensuring long-term, safe, and reliable operation.

We expect solutions that:

• enable efficient heat recovery from flue gases, including condensation-based recovery processes,
• are designed to operate in chemically aggressive (acidic) environments,
• utilize advanced corrosion-resistant materials (e.g. polymers, composites, or other innovative material solutions),
• ensure high heat exchange efficiency and stable operation under industrial conditions,
• can be integrated into existing industrial infrastructure without significant modifications.

We are looking for both innovative heat exchanger technologies and comprehensive flue gas energy recovery systems.

We are looking for innovative solutions that enable detection, localization, and quantitative assessment of steam leakages in industrial installations. The goal of the challenge is to reduce energy losses and operational costs by identifying steam leaks and accurately estimating the volume of lost medium.

Steam leakages represent a significant source of energy loss, and their effective detection and diagnosis are often challenging due to the scale of installations and environmental conditions.

We expect solutions that:

• enable detection and localization of steam leakages,
• provide high detection accuracy,
• allow estimation of the magnitude of losses (e.g. volume or energy of lost steam),
• can be deployed in various forms (e.g. handheld devices, stationary systems, mobile robots, vision-based or sensor-based solutions),
• leverage advanced data analytics to support diagnostics and decision-making,
• can be integrated with existing industrial infrastructure.

We are looking for both hardware solutions and digital systems supporting monitoring and analysis of steam losses.

We are looking for solutions leveraging advanced data analytics, Artificial Intelligence (AI), and Digital Twin models to manage and optimize compressed air systems in industrial facilities. The goal of the challenge is to significantly reduce compressed air consumption and the electricity required for its generation by improving the efficiency of production, distribution, and usage of this utility.

Compressed air is one of the key auxiliary utilities in industrial plants. Its excessive consumption, network losses, and lack of precise measurement lead to substantial operational costs. Implementing an advanced management system will enable better alignment of compressor system operation with actual demand and support the identification of optimization opportunities.

We expect solutions that:

• enable continuous monitoring of compressed air networks and their operating parameters,
• identify losses and leakages within the system,
• analyze consumption patterns and demand profiles,
• support real-time optimization of compressor system performance,
• leverage advanced data analytics, AI/ML, or Digital Twin models,
• support operators through recommendation and decision-support systems,
• allow integration with existing plant systems (e.g. EMS, PI),
• contribute to reducing resource consumption without compromising the quality and parameters of compressed air.

We are looking for system-level solutions that combine analytical capabilities with the necessary measurement infrastructure and can be deployed within existing industrial environments.

We are looking for solutions leveraging advanced data analytics and Artificial Intelligence (AI) to optimize the performance of thermal equipment in industrial installations. The goal of the challenge is to improve energy efficiency, enhance process stability, and extend equipment lifetime through intelligent, data-driven management of thermal systems.

Thermal equipment, such as evaporators, heat exchangers, and other process units, is typically energy-intensive and offers significant optimization potential.

We expect solutions that:

• enable continuous monitoring of thermal equipment operating parameters,
• analyze process data to identify inefficiencies and optimization opportunities,
• support real-time optimization or provide actionable recommendations for operators,
• leverage AI/ML algorithms or predictive models,
• contribute to reducing energy consumption and improving process efficiency,
• enhance operational stability and reduce the risk of failures,
• can be integrated with existing plant infrastructure and systems.

We are looking for system-level solutions that support both data analysis and operational decision-making in the context of thermal equipment management.

We are looking for solutions enabling the development of a Digital Twin for wind turbines to support monitoring, simulation, and optimization of wind power installations. The goal of the challenge is to create a solution capable of digitally replicating the real operation of a wind turbine in order to improve operational efficiency, increase energy production, reduce maintenance costs, and support predictive and operational decision-making processes.

As part of the pilot phase, the project is expected to deliver a basic Digital Twin model with limited functionality, along with a feasibility study for a full-scale deployment in a production environment.

The scope of the challenge includes:

• analysis and integration of available operational and environmental data
• development of a Digital Twin concept for a wind turbine
• utilization of sensors, monitoring systems, and telemetry data
• collection, processing, and analysis of process data
• development of a simulation model reflecting turbine operation
• testing and validation of the model to improve prediction quality and accuracy
• support for turbine optimization through recommendations of operating parameters aimed at maximizing energy production and minimizing maintenance costs
• preparation of the solution for further development and commercial deployment

We expect solutions leveraging advanced data analytics, AI/ML, simulation models, or IoT technologies supporting the development of modern renewable energy asset management systems.

We are looking for solutions enabling the development of a digital platform representing the MediumVoltage (MV) network based on power flow analyses, calculations, and data from smart grid monitoring and AMI infrastructure.

The goal of the challenge is to develop a Digital Twin solution capable of monitoring, simulating, and analyzing MV grid operations in near real time, while supporting operational, planning, and investment processes of the distribution system operator.

The operator has access to a broad range of data, including:

• grid models with technical parameters
• smart metering and remote reading data
• transformer station data
• information related to customers connected to the medium-voltage network

The scope of the challenge includes solutions enabling:

• development of a digital representation of the MV grid
• visualization of grid operating conditions and power flows
• execution of engineering analyses and simulations
• modeling of grid performance across different operational and load scenarios
• support for connection processes of new customers and energy sources
• support for investment planning and grid modernization activities
• analysis and development of flexibility services,
• use of advanced data analytics, AI/ML, or predictive models
• integration with existing operator systems and data sources

We are looking for digital solutions supporting the development of modern intelligent power grids and improving the efficiency of distribution system operator processes.